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Abstract

The role that stressful life events (SLEs) play in the etiology of teenage pregnancy and adverse birth outcomes, including preterm birth (PTB), has been increasingly acknowledged in the literature. However, studies in this area have revealed inconsistent findings, and existing research syntheses have not examined the temporal relationship between major SLEs (i.e., childhood maltreatment, intimate partner violence [IPV], severe mental illness [SMI], and incarceration), and common negative pregnancy outcomes. To address these limitations, five literature databases (PsycINFO, Web of Science, PubMed, Scopus, and CINAHL) were searched for longitudinal studies examining the impact of the aforementioned SLEs on teenage pregnancy or PTB. We identified 1,540 articles; 46 articles met the inclusion criteria and were included in meta-analyses. Quality assessment of included studies was conducted. Pooled odd ratios (ORs) were calculated using random effects models, and subgroup analyses were performed to investigate the moderating effects of predefined study characteristics on the effect sizes. Statistical analyses were performed in R. Experiencing any of the SLEs explored in this meta-analysis increased the risk of teenage pregnancy (pooled ORs = 1.76; 95% CI [1.56, 1.98]). While there was no significant association between childhood maltreatment and PTB, women who had experienced any form of IPV, been diagnosed with a SMI before or during pregnancy, or been incarcerated during pregnancy, had an elevated risk of having a PTB. The findings of this study emphasize the importance of screening for SLEs across the lifespan and delivering tailored integrated responses to improve birth outcomes.

Keywords

childhood maltreatment intimate partner violence incarceration preterm birth teenage pregnancy mental health meta-analysis

Introduction

Maternal exposure to stress is increasingly recognized as a risk factor for teenage pregnancy (Woodward et al., 2001) and adverse birth outcomes, such as preterm birth (PTB) (Dunkel Schetter, 2011). PTB, defined by the World Health Organisation (WHO) as a live birth before 37 weeks of gestation (WHO, 2023), remains a pressing public health concern, with a global rate of 10.6% in 2014 (Chawanpaiboon et al., 2019). However, PTB data are scant in lower-income countries (Walani, 2020) and warrant further investigation. Teenage pregnancy (pregnancy before the age of 20) was estimated to be around 41.3 births per 1,000 women globally in 2023, with variations across regions (WHO, 2024a). Both PTB and teenage pregnancy are linked to increased maternal morbidity, adverse neonatal outcomes, and long-term socioeconomic challenges (e.g., poverty, unemployment, and low educational attainment) for both mothers and their children (Cook & Cameron, 2017; Crump, 2020; Jeha et al., 2015; Luu et al., 2017). Understanding the risk factors for PTB and teenage pregnancy can help in developing effective prevention and intervention strategies to improve health outcomes across the life course.

SLEs are defined as “events that are threats to one’s social status, self-esteem, identity, or physical well-being” (Cohen et al., 2019, p. 2). The mechanisms through which SLEs influence adverse birth outcomes can be examined using general strain theory (GST; (Agnew, 1992). GST posits that SLEs cause emotional and psychological strains which can impair judgment and lead to maladaptive coping behaviors, such as unprotected sex, substance use, and neglect of prenatal care. Chronic stress also triggers physiological responses, such as elevated cortisol levels, which increase the likelihood of pregnancy complications, such as preterm labor (Hobel, 2004). The comprehensive exploration of SLEs’ impact on teenage pregnancy and PTB is crucial for understanding the interplay between these events and reproductive outcomes.

The breadth of literature on SLEs is extensive, and researchers have explored a multitude of factors that induce stress across the lifespan (Hatch & Dohrenwend, 2007). In a recent systematic review and meta-analysis, Ding et al. (2021) found that prenatal SLEs increase the risk of PTB but did not disaggregate the effects of individual SLEs. This study intends to expand the existing evidence by examining the impact of four major SLEs—abuse during childhood as well as adolescence, IPV victimization, severe mental illness (SMI), and incarceration—on teenage pregnancy and PTB. Given the high and increasing burden of these SLEs (Budd, 2024; Kern et al., 2022; National Institute of Mental Health [NIMH], 2023; WHO, 2024b), understanding their individual effects on reproductive outcomes is crucial. Identifying which SLEs have the most significant impact will help in designing targeted support services that address the most pressing risks to maternal and infant health.

Childhood abuse is a significant SLE that has been extensively studied in relation to teenage pregnancy and PTB. Psychosocial mechanisms, such as the desire to escape dysfunctional family environments or unmet intimacy needs, may prompt early sexual relationships, increasing the risk of early pregnancy, while physiological pathways, such as chronic stress and inflammation, can elevate the risk of PTB (Beers & Hollo, 2009; Strathearn et al., 2020). Neurological impairments and psychopathology stemming from abuse can impair decision-making, leading to risky sexual behaviors, including inadequate contraceptive use (Abajobir et al., 2018). Childhood sexual abuse, in particular, has attracted significant attention in the literature and has been linked to distorted sexual attitudes, heightened sexual activity, and earlier onset of sexual behavior (Noll et al., 2013), all of which increase the likelihood of teenage pregnancy (Chung et al., 2018).

IPV victimization is another prevalent SLE with significant implications for reproductive outcomes. IPV is highly prevalent both before and during pregnancy, with victims of pre-pregnancy IPV being at an increased risk of experiencing IPV during pregnancy (Silva et al., 2011). Thus, it is critical to examine the timing of IPV in understanding its impact on birth outcomes. While the evidence linking IPV to PTB is inconsistent (Auger et al., 2022; Pun et al., 2019), a few meta-analyses suggest significant associations, particularly in cross-sectional studies focused on IPV during pregnancy (Donovan et al., 2016; Hill et al., 2016). Here, the chronic stress and inflammation associated with IPV, coupled with physical harm and delayed access to prenatal care, may increase the risk of PTB (Lagdon et al., 2014; Testa et al., 2023). Additionally, adolescent IPV victims are at higher risk of teenage pregnancy, as evidenced by associations with dating violence and higher pregnancy rates during adolescence and early adulthood (Barber et al., 2018; Silverman et al., 2001). IPV can lead to teenage pregnancy through coercive control, forced sexual activity, and reduced ability to negotiate contraception (Burke et al., 2018; Madigan et al., 2014).

Serious mental illness (SMI)¹ significantly impacts reproductive health through cognitive, emotional, and social pathways. Women with SMI are more likely to engage in risky behaviors, such as substance use and unsafe sexual practices, due to impaired decision-making and emotional dysregulation (Birungi et al., 2024). These behaviors increase the risk of teenage pregnancy and PTB (Heun-Johnson et al., 2019). Chronic stress and dysregulated cortisol levels associated with SMI further exacerbate risks, contributing to pregnancy complications (Hobel, 2004). Social challenges, including stigma and isolation, coupled with barriers to accessing prenatal care and medication adherence, can amplify adverse outcomes. Despite the high prevalence of SMI among women of reproductive age (NIMH, 2023), its impact on birth outcomes remains underexplored. Existing evidence is limited to examining the link between depression and anxiety before or during pregnancy and PTB (Grigoriadis et al., 2013, 2018).

Despite the increasing rate of female incarceration globally (Budd, 2024), the impact of incarceration on reproductive outcomes remains insufficiently investigated. Incarceration may create conditions that can contribute to adverse birth outcomes. For instance, incarcerated pregnant women often encounter limited access to prenatal care (Sapkota et al., 2022), which may lead to negative maternal and neonatal consequences. Limited available evidence suggests that incarceration increases the likelihood of teenage pregnancy and PTB. For instance, youth detention has been associated with higher childbirth among girls aged 17 to 19 years old compared to those not incarcerated (Shpiegel et al., 2017). A meta-analysis found that imprisoned women were more likely to experience PTBs, compared to controls, though many studies included in the review were outdated (Knight & Plugge, 2005). Updated research is necessary to evaluate the impact of incarceration under modern obstetric practices and prison conditions.

The Current Study

Despite growing evidence, gaps remain in understanding the temporal and causal relationships between SLEs and adverse reproductive outcomes. Previous studies on childhood abuse and IPV have shown mixed results. For example, while some research indicates higher risk of teenage pregnancy (Abajobir et al., 2018) and PTB (Noll et al., 2007) among women with a history of childhood abuse, other studies have found a small or no effect (Keenan-Devlin et al., 2023; Thompson & Neilson, 2014). The impact of SLEs on reproductive outcomes is primarily derived from studies relying on retrospective or cross-sectional designs that limit causal inference (Kern et al., 2022; Madigan et al., 2014). Variations in study design, sample characteristics, and control of confounders may explain inconsistencies in findings across studies (Auger et al., 2022; Pun et al., 2019). To date, no systematic review and meta-analysis have synthesized the impact of major SLEs—including childhood abuse, IPV, SMI, and incarceration—on PTB and teenage pregnancy. This study aims to address these gaps by focusing on longitudinal studies that can establish temporal relationships. By synthesizing evidence, this research seeks to illuminate the mechanisms through which SLEs influence reproductive outcomes and guide targeted interventions to mitigate their effects.

Method

Search Strategy

Our reporting complies with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines (Moher et al., 2009). The review protocol was registered at the International Prospective Register of Systematic Reviews (PROSPERO; ID: CRD42023479138), and no similar reviews were found. A systematic search of five electronic databases, including Cumulated Index to Nursing and Allied Health Literature (CINAHL), PsycINFO (via Ovid), PubMed, Scopus, and Web of Science, was conducted on 27 October 2023. These databases encompass the diverse range of disciplines within this field. A combination of a wide range of terms was used to capture all relevant articles (see Supplemental Table 1). Lastly, a manual search of the reference lists of the included articles as well as similar reviews/meta-analyses was conducted to identify additional studies that may meet the eligibility criteria.

Study Selection and Eligibility Criteria

The study selection process was performed with Covidence (Veritas Health Innovation, 2023). MAP retrieved the articles and screened titles and abstracts of all relevant records. MAP and DS independently screened the full texts of publications and disagreements were resolved by consensus. Studies with the following criteria were eligible for inclusion: (a) all cohort studies that considered SLEs of interest as exposure variables and the risk of teenage pregnancy and/or PTB as one of the outcomes assessed and (b) publications in which odds ratios (ORs), risk ratios (RRs), or hazard ratios (HRs) and their 95% confidence intervals (CIs) were used to report the effect sizes. PTB was defined as <37 weeks of gestation and teenage pregnancy constituted a pregnancy before 20 years. Additionally, incarceration was defined as detention in either a juvenile detention facility or imprisonment in an adult correctional center. Furthermore, the studies were required to be published in English, peer-reviewed, and available as full-texts. Any reviews, meta-analyses, or abstracts and studies that could not establish a temporal relationship between SLEs and birth outcomes were excluded.

Data Extraction

A structured extraction form was created in a Microsoft Excel spreadsheet. The form included the author(s), title, year of publication, journal, country of origin, aims of the study, study population, sample size, sample characteristics, data collection tools, waves or data collection points, pregnancy outcomes, confounders accounted for, time of exposure to SLEs, analytic approach, prevalence rates of SLEs and pregnancy outcomes, and strength of associations. MAP extracted relevant data from each article and entered these in the database. DS verified the extracted data, and data were double-checked before being entered into quantitative analyses. Data extracted were discussed with other authors and any disagreements were resolved with consensus. Individual studies were included in as many separate analyses as their available data permitted. For example, if a study reported on multiple SLEs, estimates from each exposure (e.g., childhood abuse, physical abuse, sexual abuse, etc.) and selected reproductive outcomes were included. In such cases, we indicated studies as Study 1a, Study 1b, and so on.

Study Quality Assessment

The quality of included studies was examined using the Newcastle–Ottawa Scale (NOS) for quality assessment of cohort studies (Wells et al., 2000) by two independent reviewers (MAP and DS). The NOS assigns a maximum of nine points to each study: cohort selection (four points), comparability of the cohort design and analysis (two points), and adequacy of outcome measures (three points). In the current analysis, studies with scores of seven or more were considered high-quality studies, while those with scores less than seven were considered low-quality studies, consistent with previous research (Guo et al., 2023; Noll et al., 2022). Any disagreements were resolved through discussion and consensus with other authors (CT and SD). Results from the quality assessment of studies included in the meta-analysis are presented in Supplemental Table 2.

Statistical Analysis

All reported ORs, HRs, and RRs for the outcomes of interest were transformed into log ORs using natural log transformation in MS Excel (see details in Supplementary Table 4) and pooled using the DerSimonian and Laird random effects models. Due to the potential heterogeneity of the included studies, in terms of study populations and assessment methods, a random effect was used to estimate the pooled ORs and 95% CIs. The between-study heterogeneity was examined using Cochrane’s Q test and I² estimate. The heterogeneity was considered statistically significant when the p-value of the Q test was < .10 and the I² statistic was >50% (Higgins & Thompson, 2002; Higgins et al., 2003). We generated forest plots showing ORs and 95% CIs for each study and the overall random-effects pooled estimate.

Ancillary analyses consisted of publication bias assessments and implementation of the “trim and fill” method of Duval and Tweedie (to assess and adjust for the potential influence of publication bias; Duval & Tweedie, 2000). Publication bias was assessed visually by inspecting the funnel plots of estimates against the standard error (SE) of each study and by using Begg’s test and Egger’s test of funnel plot asymmetry if the number of included studies was ≥ 10. We also assessed effect size by removing outlying studies (sensitivity analyses) if more than five values were included in pooled analyses (McKay et al., 2022). When we identified significant heterogeneity (p < .05) or funnel plot asymmetry, we performed an influence analysis in which we omitted the results of one study at a time and recalculated the pooled effect estimate. We also used “find.outliers” for the dmetar package to identify outlying studies. After comparing charts from leave-one-out analysis and studies identified as outliers, we removed studies that were contributing to the significant heterogeneity and largest effect on pooled effect sizes. We then recalculated the pooled estimates from the sensitivity sample. Sensitivity analysis was also conducted by removing the studies that were rated as “low quality” in the quality assessment.

If there were five or more studies that assessed the relationship between each SLE and teenage pregnancy or PTB, we examined both methodological and demographic study-level variables to assess the potential modification effect on the pooled estimates. The variables used for moderator analyses (also known as subgroup analyses) were as follows: mean age, types of exposure, occurrence time (before pregnancy, during pregnancy, before or during pregnancy), methods of exposure assessment (questionnaire, interviews, administrative records), study location (High and upper-middle income countries [HUICs] and low-middle and low-income countries [LLICs]), publication year (before 2015 and 2015 onwards), sample size (<1,000 and ≥1,000), and adjustment of variables in final analyses. Statistical analyses were performed in R using the metagen package (Schwarzer, 2015). The univariate coefficient, standard errors, and test of moderators were reported in the moderation analysis.

Results

Characteristics of Included Studies

A total of 1,540 articles were retrieved from electronic searches (see Figure 1). After removing duplicates and screening titles and abstracts, 151 articles were selected for full-text review. Of these, 46 studies met the inclusion criteria and were included in the study (Figure 1). Supplemental Table 3 summarizes the study characteristics, including design, data collection methods, SLEs assessed, outcomes, and variable adjustments. The publication period spanned from 1996 to 2023, with about two-thirds of the articles published in the last decade, which may reflect a growing scholarly interest in this area and/or an increased availability of longitudinal data. Of the included studies, 22 were conducted in North America, 8 in Asia, 6 in Oceania, 6 in Africa, and 4 in Europe. High-income countries accounted for 32 studies, followed by 10 in lower-middle-income and 2 each in upper-middle-income and low-income countries. Most studies were prospective cohort studies (n = 34). The most studied SLE was IPV (n = 23), followed by childhood abuse (n = 12), SMI (n = 8), and incarceration (n = 3). Most studies (n = 36) assessed PTB as the outcome, while 10 assessed teenage pregnancy. Sample sizes ranged from 71 to 2,193,711. More than two-thirds of the studies (n = 35) included representative samples, however, 11 studies included individuals who are likely from disadvantaged groups (e.g., low socioeconomic status, low education, Indigenous peoples, and people from ethnic minorities).

Figure 1.

PRISMA flow diagram on the identification, screening, eligibility, and selection of articles for scoping review.

Most studies (n = 25) used administrative data to assess exposure to SLEs (e.g., linkage data, medical charts, or official records), 9 studies used questionnaires, and 12 studies conducted interviews (Jagoe et al., 2000; Taft & Watson, 2007). Most studies (n = 26) used administrative records to assess the pregnancy outcomes (e.g., independent blind assessment, record linkage, medical records, ICD-10 diagnoses), while 16 used interviews and 4 used questionnaires. Three studies used both administrative records and interviews, and two studies did not describe the method used (Afkhamzadeh et al., 2021; Jagoe et al., 2000). Lastly, most studies included samples that completed the follow-up or had drop-outs of 25% of the baseline sample or less (n = 37). Four studies did not provide information about the follow-up rate (Covington et al., 2001; Devineni et al., 2007; Jagoe et al., 2000; Neggers et al., 2004).

Outcome 1: Stressful Life Events and Teenage Pregnancy

In total, nine studies (n = 24 SLE comparisons) assessed different forms of childhood abuse or other SLEs (incarceration of young girls) and teenage pregnancy. As there was only one study that assessed the impact of other SLEs on teenage pregnancy, we excluded that from our meta-analysis. Our meta-analysis combined findings on the association between childhood abuse and teenage pregnancy.

Childhood Abuse and Teenage Pregnancy

There were eight studies (k = 23 SLE observations) that reported on the impact of childhood abuse on teenage pregnancy, with pooled OR for the random effects model being 1.83 (95% CI [1.45, 2.32], p < .01, I² = 77.6%). Five studies did not specify the type of childhood abuse. The pooled OR for the association between unspecified childhood abuse and teenage pregnancy was 1.50 (95% CI [0.97, 2.32], p > .05, I² = 88.0%). Examination of the specific types of childhood abuse revealed that childhood neglect had the strongest association with teenage pregnancy (pooled OR = 3.22), followed by childhood physical abuse (pooled OR = 1.93), and childhood sexual abuse (pooled OR = 1.60), respectively (see Figure 2).

Figure 2.

Forest plots showing pooled odds ratio and 95% CI for the experience of any SLEs and teenage pregnancy, by types of childhood abuse.

Findings from moderator analyses are included in Supplemental Table 5. Mean age was not included in the moderator analysis for any childhood abuse and teenage pregnancy as there were only four effect sizes available. Though studies conducted in 2015 or onwards had a higher odds ratio compared to studies conducted before 2015 (OR = 2.38 vs. 1.57), moderator analysis was not significant. Similar findings were observed for studies exploring different types of abuse and teenage pregnancy.

Outcome 2: Stressful Life Events and Preterm Birth

In total, 36 studies (n = 57 SLE comparisons) assessed the association between different types of SLEs and PTB. Due to significant heterogeneity across studies, we conducted separate analyses for each SLE (see Figures 3 and 4).

Figure 3.

Forest plots showing pooled odds ratio with 95% confidence intervals (CIs) for the experience of childhood abuse, any IPV, and risk of PTB for all samples using random effects model.

Figure 4.

Forest plots showing pooled odds ratio with 95% confidence intervals (CIs) for the experience of maternal SLEs and preterm birth: (A) physical IPV, (B) sexual IPV, (C) emotional IPV, (D) SMI, and (E) incarceration during pregnancy for all samples using random effects model.

Any Childhood Abuse and PTB

Despite a positive association between any childhood abuse and PTB, the association was not statistically significant (pooled OR, 1.16, 95% CI [0.90, 1.48], nine observations, I² = 37.0%). Due to an insufficient number of studies, we were unable to examine the impact of different types of childhood abuse on PTB. Publication year moderated the association between childhood abuse and PTB, with studies published before 2015 yielding a higher odds ratio compared to studies conducted in or after 2015 (2.80 vs. 1.02). Method of abuse assessment also moderated the association between childhood abuse and PTB (Q₂ = 11.0, R² = 100.0%, p = .004), with studies using administrative records yielding the largest pooled odds ratio (OR = 1.34, p = <.001) compared to studies using questionnaires (OR = 1.20, p = .735) and interviews (OR = 1.11, p = .913).

Any IPV Victimization and PTB

Mothers who had experienced any IPV had an increased risk of PTB (pooled OR, 1.33, 95% CI [1.08, 1.65], 17 observations, I² = 94.0%), with a stronger association observed among studies conducted in high-income countries than those from lower-middle-income countries (see Supplemental Table 5). Though moderator analysis was not significant, the pooled OR of studies that assessed IPV among mothers before or during pregnancy was 1.59 (95% CI [0.95, 2.64]; two observations, p = .077), which was somewhat higher than the pooled OR of studies that assessed the experience of IPV during pregnancy only (pooled OR = 1.48, 95% CI [1.16, 1.90]; 10 observations, p = .002). Studies that used administrative records to assess any IPV had higher pooled odds ratio (OR = 1.59, 95% CI [1.08, 2.35], p = .019) than studies that used interviews (OR = 1.28, p = .178) or questionnaires (OR = 1.18, p = .363).

Physical IPV and PTB

Mothers exposed to physical IPV were at increased risk of PTB (pooled OR = 2.09, 95% CI [1.66, 2.63], 10 observations, I² = 47.0%). No variables were found to moderate the association between any IPV and PTB (see Supplemental Table 5). However, the pooled OR was largest for the association between physical IPV during pregnancy and PTB (pooled OR = 2.29), followed by physical IPV at any time before pregnancy (pooled OR = 2.10). Studies that adjusted for covariates were conducted in HUICs and used interviews to assess physical IPV-reported stronger associations between physical IPV and PTB.

Sexual IPV, Emotional or Psychological IPV, and PTB

Sexual IPV was not identified as a significant predictor of PTB (pooled OR = 1.43, 95% CI [0.88, 2.33], four observations, I² = 82.0%). However, a significant positive association was found between emotional or psychological IPV and PTB (pooled OR =1.78, 95% CI [1.04, 3.08], three observations, p < .01, I² = 83.0%). Moderator analyses were not performed due to the low number of studies in these exposure groups.

SMI and PTB

Mothers diagnosed with SMI had an increased risk of PTB (pooled OR =2.21, 95% CI [1.50, 3.27], 11 observations, I² = 87.0%). Though experiencing an SMI at any time before birth significantly increased the risk of PTB (Q₂ = 6.7, R² = 37.2%, p = .040), the strongest association was found when the diagnosis was made before pregnancy (pooled OR = 3.72), followed by diagnosis during current pregnancy (pooled OR = 2.17). Model adjustment also moderated the association between SMI and teenage pregnancy (Q₁ = 34.3, R² = 93.2%, p < .001). Large ORs were obtained for studies that did not adjust for covariates (pooled OR = 6.35, 95% CI [4.12, 9.79], two observations, p < .001), while the pooled OR was far lower among studies that did adjust for covariates (pooled OR = 1.59, 95% CI [1.35, 1.88], nine observations, p < .0001).

Incarceration During Pregnancy and PTB

Mothers who were incarcerated during pregnancy were at increased risk of having a PTB (pooled OR = 1.82, 95% CI [1.30, 2.55], two observations, I² = 75.0%).

Publication Bias Assessment

Funnel plots for outcomes with at least 10 samples are provided in Supplemental Figure 1, illustrating publication bias in studies on childhood abuse and teenage pregnancy. The funnel plot was slightly right-skewed and Egger’s test was significant, suggesting the presence of publication bias. Using the trim and fill method after removing outliers, the effect size was reduced slightly while heterogeneity was reduced significantly (pooled OR = 1.86, 95% CI [1.58, 2.19], 19 comparisons, I² = 24.1%). Begg’s and Eggers’s tests were not significant.

No publication bias was found for any IPV and PTB, nor for physical IPV and PTB (p > .05). Egger’s test was significant for studies assessing the effect of SMI on PTB (p = .043), suggesting publication bias. The pooled OR decreased from 2.21 to 1.69, and the heterogeneity also decreased from 87.0% to 36.0% using the trim and fill method with outliers removed. There were insufficient studies to evaluate publication bias for other maternal SLEs, including sexual or emotional IPV and incarceration during pregnancy.

Sensitivity Analyses

Influence analyses identified outlying studies (see Supplemental Figure 2). Sensitivity analyses removing these outliers showed minimal changes in the pooled estimates but significantly reduced heterogeneity and narrowed confidence intervals (see Supplemental Table 6). After removing influential studies, the highest risk of teenage pregnancy was among mothers who experienced childhood neglect, followed by childhood sexual and emotional abuse. Physical IPV was the strongest predictor of PTB, followed by SMI. Sensitivity analyses for sexual and emotional IPV and incarceration during pregnancy were not possible due to limited studies.

Another sensitivity analysis including only those high-quality studies (Supplemental Table 6) showed a significant increase in the association between childhood abuse and teenage pregnancy, and an increased pooled OR for IPV and PTB. The pooled OR for SMI and PTB decreased slightly after removing low-quality studies.

Discussion

This systematic literature review and meta-analysis examined the longitudinal research evidence on associations between key SLEs (i.e., childhood abuse, experiences of IPV, SMI, and incarceration) and teenage pregnancy and PTB. A total of 46 peer-reviewed articles published in English between 1996 and 2023 were included.

Our findings revealed that any type of childhood abuse significantly increased the risk of teenage pregnancy, aligning with previous meta-analyses (Madigan et al., 2014; Noll et al., 2009). Notably, childhood neglect emerged as the strongest predictor of teenage pregnancy after removing low-quality studies, differing from Madigan et al. (2014), who found no significant relationship between a combined measure of emotional abuse or neglect and teenage pregnancy (Madigan et al., 2014). This discrepancy may stem from the limited number of studies and variations in study designs, with our focus on longitudinal evidence, while Madigan et al. (2014) relied on retrospective, cross-sectional studies. Additionally, recent data highlight increased referrals to the Child Protection System since 2010, and despite a decline in overall childhood abuse, there has been minimal reduction in childhood neglect (Sedlak et al., 2022). Childhood neglect impacts child’s psychological well-being and disrupts educational engagement, increasing their likelihood of engaging in risky sexual behaviors and early sexual initiation (Burke et al., 2018; Durevall et al., 2024; Ismayilova et al., 2012), which can subsequently lead to teenage pregnancy (Chung et al., 2018). Emerging evidence also supports links between childhood sexual abuse, neglect, and adverse reproductive outcomes (Lawrence et al., 2023; Pacella et al., 2023; Strathearn et al., 2020).

For PTB, findings suggest that SLEs have differential effects depending on type and timing. While childhood abuse was positively associated with PTB, the effect was not statistically significant. However, SMI had the strongest association with PTB, followed by physical IPV and incarceration. The limited number of studies prevented us from examining the impact of specific childhood abuse subtypes on PTB, but prior research aligns with our findings, showing no overall association between maternal childhood abuse and PTB, except for physically forced sexual activity (Cammack et al., 2019; Selk et al. 2016). The timing of stress exposure is critical, as pregnancy-related stress is a key risk factor for PTB (Hobel, 2004), and the effects of childhood abuse—especially non-physical forms—may diminish over time. The magnitude of health risks also varies by abuse type (Lawrence et al., 2023), underscoring the need for further investigation into how different types and the timing of childhood abuse influence PTB.

This review contributes to existing evidence by examining the timing of IPV exposure, an aspect overlooked in prior meta-analyses. Subgroup analyses revealed the highest PTB risk among women exposed to IPV before or during pregnancy, followed by IPV during pregnancy alone, consistent with previous studies (Donovan et al., 2016; Hill et al., 2016). SMI was associated with increased PTB risk at any time before birth, with the strongest effect when diagnosed before pregnancy. This could be due to higher medical comorbidities, substance use, and inadequate prenatal care, factors consistently linked to PTB (Auger et al., 2011; Baer et al., 2016; Frayne et al., 2019; Partridge et al., 2012). Finally, our findings corroborate prior research indicating that incarceration during pregnancy increases the risk of PTB (Knight & Plugge, 2005), though studies on the timing of incarceration remain scarce (Carter Ramirez et al., 2020; Walker et al., 2014), both limited to incarceration during pregnancy. Further research is warranted to understand how the timing of incarceration impacts PTB and to identify mitigation strategies.

General strain theory (GST) provides a valuable framework for interpreting these findings by explaining how chronic stressors—such as IPV, SMI, and incarceration—contribute to adverse birth outcomes through psychological distress and maladaptive coping mechanisms. GST posits that individuals who experience significant stress without coping resources are more likely to engage in high-risk behaviors or experience adverse health outcomes. In the context of PTB, IPV-induced stress (Lagdon et al., 2014), housing insecurity after leaving abusive relationships (Edin et al., 2010), and inadequate prenatal care access (Testa et al., 2023) create cumulative strain, triggering physiological responses such as inflammation and hormonal dysregulation, which increase PTB risk (Männistö et al., 2016; Partridge et al., 2012). Additionally, the direct physical harm from IPV, such as placental damage and premature rupture of membranes resulting from abdominal trauma (Leone et al., 2010; Pastor-Moreno et al., 2020), exemplifies how strain can manifest in immediate, tangible health consequences. This aligns with our IPV subtype analyses, which revealed that physical IPV significantly increased the risk of PTB.

The present study has several strengths. First, our stringent eligibility criteria ensured the inclusion of methodologically strong longitudinal cohort studies, enhancing evidence on the causal role of SLEs in adverse birth outcomes. Second, a robust methodology, including sensitivity analyses, enabled us to examine various methodological factors and assess the influence of individual studies on the pooled effect sizes. By removing outliers and low-quality studies, we generated valid and reliable findings demonstrating the negative impact of SLEs on adverse pregnancy outcomes. Third, subgroup analyses investigated how key variables influenced the pooled estimates for nearly all SLEs. Fourth, our meta-analysis synthesized global evidence, incorporating data from multiple studies across different countries, primarily from high-income countries. Given the absence of recent systematic reviews exploring the association between significant SLEs and PTB or teenage pregnancy, and the increase in relevant publications over the past decade, our study provides an updated synthesis of available research evidence.

Despite these strengths, several limitations should be acknowledged. First, while most studies used objective methods to measure SLEs and outcomes (e.g., linkage records, medical records, independent blind assessment), some relied on self-report measures or lacked methodological descriptions. This variation could have resulted in misclassification or measurement errors, potentially impacting the results. Including the method of assessment as a moderator helped examine how data collection approaches influenced findings. Second, limited studies precluded subgroup analyses for some variables, such as baseline outcome adjustment and follow-up periods, due to significant heterogeneity and insufficient information. Third, only peer-reviewed articles written in English were included. Furthermore, despite employing comprehensive search terms, most studies originated from high-income countries, limiting generalizability to lower-middle-income countries with differing socioeconomic and healthcare contexts.

Implications for Future Research and Practice

Our meta-analysis showed that SLEs significantly increase the risk of teenage pregnancy and PTB, emphasizing the need for expanded screening of maternal SLEs during prenatal visits. Routine screening for childhood abuse in primary care is also recommended to enable timely intervention and prevent early pregnancy. Gender-responsive, trauma-informed screening, and targeted responses across the life course could help mitigate these risks.

Future research should examine how childhood abuse, IPV, SMI, or incarceration contribute to adverse birth outcomes, focusing on maternal stress, health behaviors, and healthcare access as key pathways. The timing, severity, and socio-economic context of SLE exposure likely moderate these effects, making it essential to examine exposure across different life stages (e.g., childhood vs. adulthood), particularly in lower socio-economic settings where impacts may be more pronounced. Using GST, future studies can assess how the severity, timing and duration of SLE exposure shape maternal stress responses and birth outcomes, guiding the development of effective interventions. Longitudinal studies should evaluate targeted interventions, such as early support for childhood abuse survivors, pregnant women with IPV or mental illness histories to inform clinical practice and public health policy.

Despite using comprehensive search terms, our review identified only one study on teenage births among justice-involved girls (17–19 years) and found limited research from diverse settings, highlighting a critical gap. Longitudinal studies involving diverse populations are vital to explore how juvenile detention, incarceration, and related adversities contribute to teenage pregnancy and PTB, informing targeted policies and interventions.

Conclusion

Females who have experienced childhood abuse face an elevated risk of teenage pregnancy, while IPV during pregnancy—especially physical abuse—increases the likelihood of PTB. Screening for different forms of victimization and providing tailored responses from childhood through pregnancy is crucial. Additionally, adequate care for females with SMI before and during pregnancy may help reduce PTB risk. Incarceration during pregnancy also appeared to be a risk factor for PTB; however, further studies are needed to validate and confirm these findings. Given the significant health and socioeconomic impacts of teenage pregnancy and PTB, addressing these risk factors is paramount.

Critical Findings.

All forms of childhood maltreatment increase the risk of teenage pregnancy but not PTB.

Women who experience IPV are at increased risk of having a PTB, particularly those who are victimized during pregnancy.

Experiencing SMI at any time before birth increases the risk of having a PTB.

Women who are incarcerated during pregnancy have an increased risk of experiencing PTB.

Implications for Practice and Research.

Screening should be expanded for maternal experiences of SLEs during prenatal appointments.

Screening for SLEs during primary care visits throughout childhood should be implemented to identify risk factors early and prevent future exposure to negative pregnancy outcomes.

Tailored interventions, including trauma-informed responses, should be implemented to prevent the negative impacts of SLEs on teenage pregnancy and PTB.

Future research should investigate the associations between significant SLEs and adverse birth outcomes using adequate and valid assessment tools.

Populations from diverse geographical locations should be explored when investigating the association between major SLEs and adverse birth outcomes.

The mechanisms underlying the association between SLEs and PTB or teenage pregnancy should be investigated to explore potential moderating and mediating variables.

Supplemental Material

sj-docx-1-tva-10.1177_15248380251338798 – Supplemental material for Maternal Experiences of Stressful Life Events and Its Association With Teenage Pregnancy and Preterm Birth: A Systematic Review and Meta-Analysis

Supplemental material, sj-docx-1-tva-10.1177_15248380251338798 for Maternal Experiences of Stressful Life Events and Its Association With Teenage Pregnancy and Preterm Birth: A Systematic Review and Meta-Analysis by Diksha Sapkota, María Atiénzar-Prieto, Carleen Thompson and Susan Dennison in Trauma, Violence, & Abuse

Footnotes

Data Sharing Statement

All the data and findings relevant to the review are included in the manuscript and the online supplementary file.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article. D. S. is the recipient of the Griffith University Postdoctoral Research Fellowship.

ORCID iDs

Diksha Sapkota

María Atiénzar-Prieto

Carleen Thompson

Supplemental Material

Supplemental material for this article is available online.

Notes

Author Biographies

Diksha Sapkota, PhD, is a postdoctoral research fellow at Griffith Criminology Institute. Her research focuses on improving health and social outcomes for women facing domestic violence, pregnancy or postpartum challenges, and criminal justice system involvement. She enjoys interdisciplinary collaboration and is actively engaging with researchers, policymakers, and healthcare practitioners to translate her findings into actionable solutions.

María Atiénzar-Prieto is a PhD candidate at the School of Health Sciences and Social Work at Griffith University. Her research focuses on different aspects of intimate partner violence, including its nature, impacts on adult and child victim-survivors, and how people perceive different aspects related to abuse in intimate relationships.

Carleen Thompson, PhD, is co-lead of the Queensland Cross-sector Research Collaboration (QCRC), and a project investigator in the Transforming Corrections to Transform Lives Centre, in the Griffith Criminology Institute at Griffith University. Carleen’s research aims to improve the understanding of the causes and progression of antisocial behavior to drive evidence-based intervention planning that reduces offending and other harmful behaviors.

Susan Dennison, PhD, is a professor at Griffith University’s School of Criminology and Criminal Justice and Director of the Transforming Corrections to Transform Lives Centre. She focuses on transforming policies and systems to reduce the intergenerational transmission of offending and disadvantage and improve long-term outcomes for incarcerated mothers and their children.

References

*Keenan-Devlin

L. S.

Borders

A. E. B.

Freedman

Miller

G. E.

Grobman

Entringer

Simhan

Wadhwa

Buss

. (2023). Maternal exposure to childhood maltreatment and adverse birth outcomes. Scientific Reports, 13(1), 10380. https://doi.org/10.1038/s41598-023-36831-9

*Abajobir

A. A.

Kisely

Williams

Strathearn

Najman

J. M.

(2018). Risky sexual behaviors and pregnancy outcomes in young adulthood following substantiated childhood maltreatment: Findings from a prospective birth cohort study. Journal of Sex Research, 55(1), 106–119. https://doi.org/10.1080/00224499.2017.1368975

*Afkhamzadeh

Rahmani

Yaghubi

Ghadrdan

Faraji

(2021). Adverse perinatal outcomes of intimate partner violence during pregnancy. International Journal of Human Rights in Healthcare, 14(5), 465–476. https://doi.org/10.1108/IJHRH-08-2019-0067

*Auger

Low

Lee

G. E.

Ayoub

Luu

T. M.

(2022). Pregnancy outcomes of women hospitalized for physical assault, sexual assault, and intimate partner violence. Journal of Interpersonal Violence, 37(13/14), NP11135–NP11135. https://doi.org/10.1177/0886260520985496

*Cammack

A. L.

Hogue

C. J.

Drews-Botsch

C. D.

Kramer

M. R.

Pearce

B. D.

(2019). Associations between maternal exposure to child abuse, preterm birth, and very preterm birth in young, nulliparous women. Maternal and Child Health Journal, 23(6), 847–857. https://doi.org/10.1007/s10995-018-02709-w

*Carter Ramirez

Liauw

Costescu

Holder

Kouyoumdjian

F. G

. (2020). Infant and maternal outcomes for women who experience imprisonment in Ontario, Canada: A retrospective cohort study. Journal of Obstetrics and Gynaecology Canada, 42(4), 462–472. https://doi.org/10.1016/j.jogc.2019.11.068

*Chen

P.-H.

Rovi

Vega

M. L.

Barrett

Pan

K.-Y.

Johnson

M. S.

(2017). Birth outcomes in relation to intimate partner violence. Journal of the National Medical Association, 109(4), 238–245. https://doi.org/10.1016/j.jnma.2017.06.017

*Covington

D. L.

Justason

B. J.

Wright

L. N.

(2001). Severity, manifestations, and consequences of violence among pregnant adolescents. Journal of Adolescent Health, 28(1), 55–61. https://doi.org/10.1016/s1054-139x(00)00154-3

*Dai

Gui

Fan

Liu

Han

Sun

Shen

Bai

Liu

(2022). Effects of psychiatric disorders on ultrasound measurements and adverse perinatal outcomes in Chinese pregnant women: A ten-year retrospective cohort study. Journal of Psychiatric Research, 156, 361–371. https://doi.org/10.1016/j.jpsychires.2022.10.046

10.

*Dolatian

Sharifi

Mahmoodi

(2018). Relationship of socioeconomic status, psychosocial factors, and food insecurity with preterm labor: A longitudinal study. International Journal of Reproductive BioMedicine, 16(9), 563–570. https://doi.org/10.29252/ijrm.16.9.563

11.

*Ellman

L. M.

Huttunen

Lonnqvist

Cannon

T. D.

(2007). The effects of genetic liability for schizophrenia and maternal smoking during pregnancy on obstetric complications. Schizophrenia Research, 93(1–3), 229–236. https://doi.org/10.1016/j.schres.2007.03.004

12.

*Frayne

Nguyen

Allen

Hauck

Liira

Vickery

(2019). Obstetric outcomes for women with severe mental illness: 10 years of experience in a tertiary multidisciplinary antenatal clinic. Archives of Gynecology & Obstetrics, 300(4), 889–896. https://doi.org/10.1007/s00404-019-05258-x

13.

*Fried

L. E.

Cabral

Amaro

Aschengrau

(2008). Lifetime and during pregnancy experience of violence and the risk of low birth weight and preterm birth. Journal of Midwifery & Women’s Health, 53(6), 522–528. https://doi.org/10.1016/j.jmwh.2008.07.018

14.

*Garwood

S. K.

Gerassi

Jonson-Reid

Plax

Drake

(2015). More than poverty: The effect of child abuse and neglect on teen pregnancy risk. Journal of Adolescent Health, 57(2), 164–168. https://doi.org/10.1016/j.jadohealth.2015.05.004

15.

*Hoang

T. N.

Van

T. N.

Gammeltoft

T. D, W. M.

Nguyen Thi Thuy

Rasch

(2016). Association between intimate partner violence during pregnancy and adverse pregnancy outcomes in Vietnam: A prospective cohort study. PLoS One, 11(9), e0162844. https://doi.org/10.1371/journal.pone.0162844

16.

*Jagoe

Magann

E. F.

Chauhan

S. P.

Morrison

J. C.

(2000). The effects of physical abuse on pregnancy outcomes in a low-risk obstetric population. American Journal of Obstetrics & Gynecology, 182(5), 1067–1069. https://doi.org/10.1067/mob.2000.105436

17.

*Kugler

K. C.

Guastaferro

Shenk

C. E.

Beal

S. J.

Zadzora

K. M.

Noll

J. G.

(2019). The effect of substantiated and unsubstantiated investigations of child maltreatment and subsequent adolescent health. Child Abuse and Neglect, 87, 112–119. https://doi.org/10.1016/j.chiabu.2018.06.005

18.

*Larsen

Pintye

Abuna

Bhat

Dettinger

J. C.

Gomez

Marwa

M. M.

Ngumbau

Odhiambo

Phipps

A. I.

Richardson

B. A.

Watoyi

Stern

Kinuthia

John-Stewart

(2023). Risks of adverse perinatal outcomes in relation to maternal depressive symptoms: A prospective cohort study in Kenya. Paediatric Perinatal Epidemioly, 37(6), 489–504. https://doi.org/10.1111/ppe.12978

19.

*Lipsky

Holt

V. L.

Easterling

T. R.

Critchlow

C. W.

(2003). Impact of police-reported intimate partner violence during pregnancy on birth outcomes. Obstetrics & Gynecology, 102(3), 557–564. https://doi.org/10.1016/s0029-7844(03)00573-8

20.

*Melaku

Getahun

S. B.

Abebe

Shumye

Semagn

(2023). The association between domestic violence and adverse pregnancy outcomes in pregnant women seeking antenatal care at public hospitals in Gedeo Zone: A prospective cohort study. Journal of Multidisciplinary Healthcare, 16, 1833–1843. https://doi.org/10.2147/JMDH.S419473

21.

*Najjarzadeha

Mohammad-Alizadeh-Charandabi

Abbasalizadeh

Asghari-Jafarabadi

Mirghafourvand

(2022). Technology-free predictors of preterm birth in singleton women with threatened preterm labor: A prospective cohort study. BMC Pregnancy & Childbirth, 22(1), 1–9. https://doi.org/10.1186/s12884-022-05155-3

22.

*Neggers

Goldenberg

Cliver

Hauth

(2004). Effects of domestic violence on preterm birth and low birth weight. Acta Obstetricia Et Gynecologica Scandinavica, 83(5), 455–460. https://doi.org/10.1111/j.0001-6349.2004.00458.x

23.

*Negriff

Schneiderman

J. U.

Trickett

P. K.

(2015). Child maltreatment and sexual risk behavior: Maltreatment types and gender differences. Journal of Developmental and Behavioral Pediatrics, 36(9), 708–716. https://doi.org/10.1097/DBP.0000000000000204

24.

*Nilsson

Lichtenstein

Cnattingius

Murray

R. M.

Hultman

C. M.

(2002). Women with schizophrenia: Pregnancy outcome and infant death among their offspring. Schizophrenia Research, 58(2–3), 221–229. https://doi.org/10.1016/s0920-9964(01)00370-x

25.

*Noll

J. G.

Shenk

C. E.

(2013). Teen birth rates in sexually abused and neglected females. Pediatrics, 131(4), E1181–E1187. https://doi.org/10.1542/peds.2012-3072

26.

*Noll

J. G.

Schulkin

Trickett

P. K.

Susman

E. J.

Breech

Putnam

F. W.

(2007). Differential pathways to preterm delivery for sexually abused and comparison women. Journal of Pediatric Psychology, 32(10), 1238–1248. https://doi.org/10.1093/jpepsy/jsm046

27.

*Okunola

T. O.

Awoleke

J. O.

Olofinbiyi

B. A.

Rosiji

B. O.

Omoya

Olubiyi

A. O.

(2021). Adverse birth outcomes among women exposed to intimate partner violence in pregnancy in Ikere-Ekiti, South-west Nigeria: A prospective cohort study. European Journal of Obstetrics & Gynecology & Reproductive Biology, 267, 186–191. https://doi.org/10.1016/j.ejogrb.2021.11.017

28.

*Orr

Kelty

Fisher

O’Donnell

Glauert

Preen

D. B.

(2022). The lasting impact of family and domestic violence on neonatal health outcomes. Birth: Issues in Perinatal Care, 50(3), 578–586. https://doi.org/10.1111/birt.12682

29.

*Pun

K. D.

Rishal

Darj

Infanti

J. J.

Shrestha

Lukasse

Schei

(2019). Domestic violence and perinatal outcomes – A prospective cohort study from Nepal. BMC Public Health, 19(1), 1–9. https://doi.org/10.1186/s12889-019-6967-y

30.

*Sania

Brittain

Phillips

T. K.

Zerbe

Ronan

Myer

Abrams

E. J.

(2017). Effect of alcohol consumption and psychosocial stressors on preterm and small-for-gestational-age births in HIV-infected women in South Africa: A cohort study. BMJ Open, 7(3), e014293. https://doi.org/10.1136/bmjopen-2016-014293

31.

*Shneyderman

Kiely

(2013). Intimate partner violence during pregnancy: Victim or perpetrator? Does it make a difference? BJOG: An International Journal of Obstetrics and Gynaecology, 120(11), 1375–1385. https://doi.org/10.1111/1471-0528.12357

32.

*Shpiegel

Cascardi

Dineen

(2017). A social ecology analysis of childbirth among females emancipating from foster care. Journal of Adolescent Health, 60(5), 563–569. https://doi.org/10.1016/j.jadohealth.2016.09.013

33.

*Sigalla

G. N.

Mushi

Meyrowitsch

D. W.

Manongi

Rogathi

J. J.

Gammeltoft

Rasch

(2017). Intimate partner violence during pregnancy and its association with preterm birth and low birth weight in Tanzania: A prospective cohort study. PLoS One, 12(2), e0172540. https://doi.org/10.1371/journal.pone.0172540

34.

*Simoila

Isometsä

Gissler

Suvisaari

Halmesmäki

Lindberg

(2018). Obstetric and perinatal health outcomes related to schizophrenia: A national register-based follow-up study among Finnish women born between 1965 and 1980 and their offspring. European Psychiatry, 52, 68–75. https://doi.org/10.1016/j.eurpsy.2018.04.001

35.

*Sit

Luther

Dills

J. L.

Eng

Wisniewski

Wisner

K. L.

(2014). Abnormal screening for gestational diabetes, maternal mood disorder, and preterm birth. Bipolar Disorders, 16(3), 308–317. https://doi.org/10.1111/bdi.12129

36.

*Taft

A. J.

Watson

L. F.

(2007). Termination of pregnancy: Associations with partner violence and other factors in a national cohort of young Australian women. Australian and New Zealand Journal of Public Health, 31(2), 135–142. https://doi.org/10.1111/j.1753-6405.2007.00031.x

37.

*Thompson

Neilson

E. C.

(2014). Early parenting: The roles of maltreatment, trauma symptoms, and future expectations. Journal of Adolescence, 37(7), 1099–1108. https://doi.org/10.1016/j.adolescence.2014.08.003

38.

*Van Ngo

Gammeltoft

Nguyen

H. T. T.

Meyrowitsch

D. W.

Rasch

. (2018). Antenatal depressive symptoms and adverse birth outcomes in Hanoi, Vietnam. PLoS One, 13(11), e0206650. https://doi.org/10.1371/journal.pone.0206650

39.

*Vigod

S. N.

Kurdyak

P. A.

Dennis

C. L.

Gruneir

Newman

Seeman

M. V.

Rochon

P. A.

Anderson

G. M.

Grigoriadis

Ray

J. G.

(2014). Maternal and newborn outcomes among women with schizophrenia: A retrospective population-based cohort study. BJOG, 121(5), 566–574. https://doi.org/10.1111/1471-0528.12567

40.

*Walker

J. R.

Hilder

Levy

M. H.

Sullivan

E. A.

(2014). Pregnancy, prison and perinatal outcomes in New South Wales, Australia: A retrospective cohort study using linked health data. BMC Pregnancy and Childbirth, 14(11), 214. https://doi.org/10.1186/1471-2393-14-214

41.

*Wassie

S. T.

Ejigu

A. G.

Tilahun

A. G.

Lambyo

S. H. M.

(2023). The impact of intimate partner violence on adverse birth outcomes in public health facilities. A prospective cohort study. Midwifery, 126, 103815. https://doi.org/10.1016/j.midw.2023.103815

42.

*Widom

C. S.

Kuhns

J. B.

(1996). Childhood victimization and subsequent risk for promiscuity, prostitution, and teenage pregnancy: A prospective study. American Journal of Public Health, 86(11), 1607–1612. https://doi.org/10.2105/AJPH.86.11.1607

43.

*Woodward

Fergusson

D. M.

Horwood

L. J.

(2001). Risk factors and life processes associated with teenage pregnancy: Results of a prospective study from birth to 20 years. Journal of Marriage and Family, 63(4), 1170–1184. https://doi.org/10.1111/j.1741-3737.2001.01170.x

44.

*Yin

Ludvigsson

J. F.

Åden

Risnes

Persson

Reichenberg

Silverman

M. E.

Kajantie

Sandin

(2023). Paternal and maternal psychiatric history and risk of preterm and early term birth: A nationwide study using Swedish registers. Plos Medicine, 20(7), e1004256. https://doi.org/10.1371/journal.pmed.1004256

45.

Agnew

(1992). Foundation for a general strain theory of crime and delinquency. Criminology, 30(1), 47–88.

46.

Auger

T. U. N.

Park

A. L.

Luo

Z.-C.

(2011). Association between maternal comorbidity and preterm birth by severity and clinical subtype: Retrospective cohort study. BMC Pregnancy and Childbirth, 11(1), 67. https://doi.org/10.1186/1471-2393-11-67

47.

Baer

R. J.

Chambers

C. D.

Bandoli

Jelliffe-Pawlowski

L. L.

(2016). Risk of preterm birth by subtype among Medi-Cal participants with mental illness. American Journal of Obstetrics & Gynecology, 215(4), 519-e1. https://doi.org/10.1016/j.ajog.2016.06.017

48.

Barber

J. S.

Kusunoki

Gatny

H. H.

Budnick

(2018). The dynamics of intimate partner violence and the risk of pregnancy during the transition to adulthood. American Sociological Review, 83(5), 1020–1047. https://doi.org/10.1177/0003122418795856

49.

Beers

L. A. S.

Hollo

R. E.

(2009). Approaching the adolescent-headed family: A review of teen parenting. Current Problems in Pediatric and Adolescent Health Care, 39(9), 216–233. https://doi.org/10.1016/j.cppeds.2009.09.001

50.

Birungi

Ssebunnya

Kiwanuka

Nakasujja

Kinyanda

(2024). Vulnerability to risky sexual behavior among patients with severe mental illness in Uganda. Discover Social Science and Health, 4(1), 17. https://doi.org/10.1007/s44155-024-00071-7

51.

Budd

M. K.

(2024). Incarcerated women and girls. The Sentencing Project Retrieved 23/02/2025, from https://www.sentencingproject.org/fact-sheet/incarcerated-women-and-girls/

52.

Burke

Nic Gabhainn

Kelly

(2018). Socio-demographic, health and lifestyle factors influencing age of sexual initiation among adolescents. International Journal of Environmental Research and Public Health, 15(9), 1851. https://doi.org/10.3390/ijerph15091851

53.

Chawanpaiboon

Vogel

J. P.

Moller

A.-B.

Lumbiganon

Petzold

Hogan

Landoulsi

Jampathong

Kongwattanakul

Laopaiboon

Lewis

Rattanakanokchai

Teng

D. N.

Thinkhamrop

Watananirun

Zhang

Zhou

Gülmezoglu

A. M.

(2019). Global, regional, and national estimates of levels of preterm birth in 2014: A systematic review and modelling analysis. The Lancet Global Health, 7(1), e37–e46. https://doi.org/10.1016/S2214-109X(18)30451-0

54.

Chung

H. W.

Kim

E. M.

Lee

J.-E.

(2018). Comprehensive understanding of risk and protective factors related to adolescent pregnancy in low- and middle-income countries: A systematic review. Journal of Adolescence, 69, 180–188. https://doi.org/10.1016/j.adolescence.2018.10.007

55.

Cohen

Murphy

M. L. M.

Prather

A. A.

(2019). Ten surprising facts about stressful life events and disease risk. Annual Review of Psychology, 70, 577–597. https://doi.org/10.1146/annurev-psych-010418-102857

56.

Cook

S. M. C.

Cameron

S. T.

(2017). Social issues of teenage pregnancy. Obstetrics, Gynaecology & Reproductive Medicine, 27(11), 327–332. https://doi.org/10.1016/j.ogrm.2017.08.005

57.

Crump

(2020). An overview of adult health outcomes after preterm birth. Early Human Development, 150, 105187. https://doi.org/10.1016/j.earlhumdev.2020.105187

58.

Devineni

Kumari

S. S.

Sodumu

Garg

(2007). Effects of intimate partner violence on pregnancy outcome. Journal of SAFOG, 10(2), 142–148. https://doi.org/10.5005/jp-journals-10006-1578

59.

Ding

Liang

Zhao

Zhang

Han

Sun

(2021). The impact of prenatal stressful life events on adverse birth outcomes: A systematic review and meta-analysis. Journal of Affective Disorders, 287, 406–416. https://doi.org/10.1016/j.jad.2021.03.083

60.

Donovan

Spracklen

Schweizer

Ryckman

Saftlas

(2016). Intimate partner violence during pregnancy and the risk for adverse infant outcomes: A systematic review and meta-analysis. BJOG: An International Journal of Obstetrics & Gynaecology, 123(8), 1289–1299. https://doi.org/10.1111/1471-0528.13928

61.

Dunkel Schetter

. (2011). Psychological science on pregnancy: Stress processes, biopsychosocial models, and emerging research issues. Annual Review of Psychology, 62, 531–558. https://doi.org/10.1146/annurev.psych.031809.130727

62.

Durevall

Cowden

R. G.

Beckett

Kharsany

A. B. M.

Lewis

George

Cawood

Khanyile

Govender

(2024). Associations of social support with sexual practices, health behaviours, and health outcomes among adolescent girls and young women: Evidence from a longitudinal study in KwaZulu-Natal, South Africa. International Journal of Behavioral Medicine, 31(4), 620–630. https://doi.org/10.1007/s12529-023-10199-6

63.

Duval

Tweedie

(2000). Trim and fill: A simple funnel-plot–based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56(2), 455–463. https://doi.org/10.1111/j.0006-341X.2000.00455.x

64.

Edin

K. E.

Dahlgren

Lalos

Högberg

(2010). “Keeping up a front”: Narratives about intimate partner violence, pregnancy, and antenatal care. Violence Against Women, 16(2), 189–206. https://doi.org/10.1177/1077801209355703

65.

Grigoriadis

Graves

Peer

Mamisashvili

Tomlinson

Vigod

S. N.

Dennis

C.-L.

Steiner

Brown

Cheung

Dawson

Rector

N. A.

Guenette

Richter

(2018). Maternal anxiety during pregnancy and the association with adverse perinatal outcomes: Systematic review and meta-analysis. The Journal of Clinical Psychiatry, 79(5), 17r12011. https://doi.org/10.4088/JCP.17r12011

66.

Grigoriadis

VonderPorten

E. H.

Mamisashvili

Tomlinson

Dennis

C.-L.

Koren

Steiner

Mousmanis

Cheung

Radford

Martinovic

Ross

L. E.

(2013). The impact of maternal depression during pregnancy on perinatal outcomes: A systematic review and meta-analysis. The Journal of Clinical Psychiatry, 74(4), 8615. https://doi.org/10.4088/JCP.12r07968

67.

Guo

Lin

Zhou

(2023). Risk factors for delirium among hospitalized adults with COVID-19: A systematic review and meta-analysis of cohort studies. International Journal of Nursing Studies, 148, 104602. https://doi.org/10.1016/j.ijnurstu.2023.104602

68.

Hatch

S. L.

Dohrenwend

B. P.

(2007). Distribution of traumatic and other stressful life events by race/ethnicity, gender, SES and age: A review of the research. American Journal of Community Psychology, 40(3–4), 313–332. https://doi.org/10.1007/s10464-007-9134-z

69.

Heun-Johnson

Seabury

S. A.

Menchine

Claudius

Axeen

Lakshmanan

(2019). Association between maternal serious mental illness and adverse birth outcomes. Journal of Perinatology, 39(5), 737–745. https://doi.org/10.1038/s41372-019-0346-5

70.

Higgins

J. P.

Thompson

S. G.

(2002). Quantifying heterogeneity in a meta-analysis. Statistics in Medicine, 21(11), 1539–1558. https://doi.org/10.1002/sim.1186

71.

Higgins

J. P.

Thompson

S. G.

Deeks

J. J.

Altman

D. G.

(2003). Measuring inconsistency in meta-analyses. BMJ, 327(7414), 557–560. https://doi.org/10.1136/bmj.327.7414.557

72.

Hill

Pallitto

McCleary-Sills

Garcia-Moreno

(2016). A systematic review and meta-analysis of intimate partner violence during pregnancy and selected birth outcomes. International Journal of Gynecology & Obstetrics, 133(3), 269–276. https://doi.org/10.1016/j.ijgo.2015.10.023

73.

Hobel

C. J.

(2004). Stress and preterm birth. Clinical Obstetrics and Gynecology, 47(4), 856–880.

74.

Ismayilova

Ssewamala

F. M.

Karimli

(2012). Family support as a mediator of change in sexual risk-taking attitudes among orphaned adolescents in rural Uganda. Journal of Adolescent Health, 50(3), 228–235. https://doi.org/10.1016/j.jadohealth.2011.06.008

75.

Jeha

Usta

Ghulmiyyah

Nassar

(2015). A review of the risks and consequences of adolescent pregnancy. Journal of Neonatal-Perinatal Medicine, 8(1), 1–8. https://doi.org/10.3233/NPM-15814038

76.

Kern

Khoury

Frederickson

Langevin

(2022). The associations between childhood maltreatment and pregnancy complications: A systematic review and meta-analysis. Journal of Psychosomatic Research, 160, 110985. https://doi.org/10.1016/j.jpsychores.2022.110985

77.

Knight

Plugge

(2005). The outcomes of pregnancy among imprisoned women: A systematic review. BJOG: An International Journal of Obstetrics & Gynaecology, 112(11), 1467–1474. https://doi.org/10.1111/j.1471-0528.2005.00749.x

78.

Lagdon

Armour

Stringer

(2014). Adult experience of mental health outcomes as a result of intimate partner violence victimisation: A systematic review. European Journal of Psychotraumatology, 5(1), 24794. https://doi.org/10.3402/ejpt.v5.24794

79.

Lawrence

D. M.

Hunt

Mathews

Haslam

D. M.

Malacova

Dunne

M. P.

Erskine

H. E.

Higgins

D. J.

Finkelhor

Pacella

Meinck

Thomas

H. J.

Scott

J. G.

(2023). The association between child maltreatment and health risk behaviours and conditions throughout life in the Australian Child Maltreatment Study. Medical Journal of Australia, 218, S34–S39. https://doi.org/10.5694/mja2.51877

80.

Leone

J. M.

Lane

S. D.

Koumans

E. H.

DeMott

Wojtowycz

M. A.

Jensen

Aubry

R. H.

(2010). Effects of intimate partner violence on pregnancy trauma and placental abruption. Journal of Women’s Health, 19(8), 1501–1509. https://doi.org/10.1089/jwh.2009.1716

81.

Luu

T. M.

Mian

M. O. R.

Nuyt

A. M.

(2017). Long-term impact of preterm birth: Neurodevelopmental and physical health outcomes. Clinics in Perinatology, 44(2), 305–314. https://doi.org/10.1016/j.clp.2017.01.003

82.

Madigan

Wade

Tarabulsy

Jenkins

J. M.

Shouldice

(2014). Association between abuse history and adolescent pregnancy: A meta-analysis. Journal of Adolescent Health, 55(2), 151–159. https://doi.org/10.1016/j.jadohealth.2014.05.002

83.

Männistö

Mendola

Kiely

O’Loughlin

Werder

Chen

Ehrenthal

D. B.

Grantz

K. L.

(2016). Maternal psychiatric disorders and risk of preterm birth. Annals of Epidemiology, 26(1), 14–20. https://doi.org/10.1016/j.annepidem.2015.09.009

84.

McKay

M. T.

Kilmartin

Meagher

Cannon

Healy

Clarke

M. C.

(2022). A revised and extended systematic review and meta-analysis of the relationship between childhood adversity and adult psychiatric disorder. Journal of Psychiatric Research, 156, 268–283. https://doi.org/10.1016/j.jpsychires.2022.10.015

85.

Moher

Liberati

Tetzlaff

Altman

D. G.

& PRISMA Group* t. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Annals of Internal Medicine, 151(4), 264–269. https://doi.org/10.1136/bmj.b2535

86.

National Institute of Mental Health (NIMH). (2023). Mental Illness. https://www.nimh.nih.gov/health/statistics/mental-illness#:~:text=Prevalence%20of%20Serious%20Mental%20Illness%20(SMI),-Figure%203%20shows&text=The%20prevalence%20of%20SMI%20was,50%20and%20older%20(2.5%25)

87.

Noll

J. G.

Shenk

C. E.

Putnam

K. T.

(2009). Childhood sexual abuse and adolescent pregnancy: A meta-analytic update. Journal of Pediatric Psychology, 34(4), 366–378. https://doi.org/10.1093/jpepsy/jsn098

88.

Noll

Mitham

Moran

Mallows

(2022). Identifying current uses of return to work screening tests and their effectiveness of reducing the risk of reinjury in athletic occupations–A systematic review. Physical Therapy in Sport, 58, 141–150. https://doi.org/10.1016/j.ptsp.2022.10.010

89.

Pacella

Nation

Mathews

Scott

J. G.

Higgins

D. J.

Haslam

D. M.

Dunne

M. P.

Finkelhor

Meinck

Erskine

H. E.

Thomas

H. J.

Malacova

Lawrence

D. M.

Monks

(2023). Child maltreatment and health service use: Findings of the Australian Child Maltreatment Study. Medical Journal of Australia, 218, S40–S46. https://doi.org/10.5694/mja2.51892

90.

Partridge

Balayla

Holcroft

C. A.

Abenhaim

H. A.

(2012). Inadequate prenatal care utilization and risks of infant mortality and poor birth outcome: A retrospective analysis of 28,729,765 US deliveries over 8 years. American Journal of Perinatology, 29(10), 787–794. https://doi.org/10.1055/s-0032-1316439

91.

Pastor-Moreno

Ruiz-Pérez

Henares-Montiel

Escribà-Agüir

Higueras-Callejón

Ricci-Cabello

(2020). Intimate partner violence and perinatal health: A systematic review. BJOG: An International Journal of Obstetrics & Gynaecology, 127(5), 537–547. https://doi.org/10.1111/1471-0528.16084

92.

Sapkota

Dennison

Allen

Gamble

Williams

Malope-Rwodzi

Baar

Ransley

Renae McGee

(2022). Navigating pregnancy and early motherhood in prison: a thematic analysis of mothers’ experiences. Health & Justice, 10(1), 32. https://doi.org/10.1186/s40352-022-00196-4

93.

Schwarzer

(2015). meta: General package for meta-analysis. R package version 4.3-2. Computer software.

94.

Sedlak

A. J.

Heaton

Evans

(2022). Trends in child abuse reporting. In Handbook of Child Maltreatment (pp. 3–34). Springer.

95.

Selk

S. C.

Rich-Edwards

J. W.

Koenen

Kubzansky

L. D.

(2016). An observational study of type, timing, and severity of childhood maltreatment and preterm birth. Journal of Epidemiology and Community Health, 70(6), 589–595. https://doi.org/10.1136/jech-2015-206304

96.

Silva

E. P.

Ludermir

A. B.

Araújo

T. V. B. d.

Valongueiro

S. A.

(2011). Frequency and pattern of intimate partner violence before, during and after pregnancy. Revista de Saude Publica, 45, 1044–1053. https://doi.org/10.1590/s0034-89102011005000074

97.

Silverman

J. G.

Raj

Mucci

L. A.

Hathaway

J. E.

(2001). Dating violence against adolescent girls and associated substance use, unhealthy weight control, sexual risk behavior, pregnancy, and suicidality. JAMA, 286(5), 572–579. https://doi.org/10.1001/jama.286.5.572

98.

Smith

(1996). The link between childhood maltreatment and teenage pregnancy. Social Work Research, 20(3), 131–141. https://doi.org/10.1093/swr/20.3.131

99.

Strathearn

Giannotti

Mills

Kisely

Najman

Abajobir

(2020). Long-term cognitive, pychological, and health outcomes associated with child abuse and neglect. Pediatrics, 146(4), e20200438. https://doi.org/10.1542/peds.2020-0438

100.

Testa

Lee

Semenza

D. C.

Jackson

D. B.

Ganson

K. T.

Nagata

J. M.

(2023). Intimate partner violence and barriers to prenatal care. Social Science & Medicine, 320, 115700. https://doi.org/10.1016/j.socscimed.2023.115700

101.

Veritas Health Innovation. (2023). Covidence systematic review software. https://www.covidence.org

102.

Walani

S. R.

(2020). Global burden of preterm birth. International Journal of Gynecology & Obstetrics, 150(1), 31–33. https://doi.org/10.1002/ijgo.13195

103.

Wells

G. A.

Shea

O’Connell

Peterson

Welch

Losos

Tugwell

(2000). The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. http://www.ohri.ca/programs/clinical_epidemiology/oxford.htm (Accessed on 1st May 2024).

104.

World Health Organisation (WHO). (2023). Preterm birth. Key facts. https://www.who.int/news-room/fact-sheets/detail/preterm-birth

105.

World Health Organisation (WHO). (2024a). Adolescent pregnancy. Key facts. https://www.who.int/news-room/fact-sheets/detail/adolescent-pregnancy

106.

World Health Organisation (WHO). (2024b). Violence against women. Key facts. https://www.who.int/news-room/fact-sheets/detail/violence-against-women

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